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Real-time $R_t$ of COVID-19 pandemic in Texas (Until 6/28)

This report estimates the county level real-time effective production number ($R_t$) of the COVID-19 pandemic in Texas, based on data from the Texas Health and Human Services. This report is updated daily with the most recent version available at the ICTR website.

This report is created and maintained by data scientists from the Institute for Clinical & Translational Research, Baylor College of Medicine, with an algorithm that is based on Kevin Systrom's work for the US data. Please refer to the original report for details.

Daily new cases and real time $R_t$ for Texas Medical Center

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ImportError                               Traceback (most recent call last)
<ipython-input-26-b5ca82b63586> in <module>
      2 import os
      3 latest_data = sorted([x for x in os.listdir('TMC') if x.startswith('Total Tests') and x.endswith('xlsx')])[-1]
----> 4 tmc_data = pd.read_excel(f'TMC/{latest_data}')
      5 tmc_data = tmc_data.dropna()
      6 tmc_data = tmc_data[tmc_data["Collected Date"] != "Grand Total"]

/opt/conda/lib/python3.7/site-packages/pandas/util/_decorators.py in wrapper(*args, **kwargs)
    294                 )
    295                 warnings.warn(msg, FutureWarning, stacklevel=stacklevel)
--> 296             return func(*args, **kwargs)
    297 
    298         return wrapper

/opt/conda/lib/python3.7/site-packages/pandas/io/excel/_base.py in read_excel(io, sheet_name, header, names, index_col, usecols, squeeze, dtype, engine, converters, true_values, false_values, skiprows, nrows, na_values, keep_default_na, na_filter, verbose, parse_dates, date_parser, thousands, comment, skipfooter, convert_float, mangle_dupe_cols)
    302 
    303     if not isinstance(io, ExcelFile):
--> 304         io = ExcelFile(io, engine=engine)
    305     elif engine and engine != io.engine:
    306         raise ValueError(

/opt/conda/lib/python3.7/site-packages/pandas/io/excel/_base.py in __init__(self, path_or_buffer, engine)
    865         self._io = stringify_path(path_or_buffer)
    866 
--> 867         self._reader = self._engines[engine](self._io)
    868 
    869     def __fspath__(self):

/opt/conda/lib/python3.7/site-packages/pandas/io/excel/_xlrd.py in __init__(self, filepath_or_buffer)
     19         """
     20         err_msg = "Install xlrd >= 1.0.0 for Excel support"
---> 21         import_optional_dependency("xlrd", extra=err_msg)
     22         super().__init__(filepath_or_buffer)
     23 

/opt/conda/lib/python3.7/site-packages/pandas/compat/_optional.py in import_optional_dependency(name, extra, raise_on_missing, on_version)
    108     except ImportError:
    109         if raise_on_missing:
--> 110             raise ImportError(msg) from None
    111         else:
    112             return None

ImportError: Missing optional dependency 'xlrd'. Install xlrd >= 1.0.0 for Excel support Use pip or conda to install xlrd.
---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-28-94df48a8a569> in <module>
      1 fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(15, 5))
      2 
----> 3 tmc_original, tmc_smoothed = prepare_cases(tmc_cases, cutoff=14, smooth_days=param_days, smooth_std=param_std)
      4 plot_tmc_cases(tmc_cases, axes[0], smooth_days=param_days, smooth_std=param_std)
      5 

NameError: name 'tmc_cases' is not defined
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Here are estimated $R_t$ in the past 15 days:

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Execution using papermill encountered an exception here and stopped:

======= >>>>>>> a8b82171ef2e915104e159d47b401640b3583c90
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---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-29-cc80061d9bfa> in <module>
----> 1 tmc_result.tail(n=15)

NameError: name 'tmc_result' is not defined
=======
ML Low_90 High_90
Collected Date
2020-08-23 0.74 0.46 0.97
2020-08-24 0.74 0.45 0.97
2020-08-25 0.75 0.47 0.99
2020-08-26 0.75 0.46 0.99
2020-08-27 0.76 0.47 1.00
2020-08-28 0.77 0.50 1.03
2020-08-29 0.78 0.49 1.03
2020-08-30 0.81 0.52 1.06
2020-08-31 0.84 0.56 1.10
2020-09-01 0.87 0.56 1.11
2020-09-02 0.86 0.56 1.11
2020-09-03 0.84 0.54 1.09
2020-09-04 0.80 0.50 1.05
2020-09-05 0.75 0.47 1.02
2020-09-06 0.70 0.40 0.96
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Daily new cases and real time $R_t$ for Harris County

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Here are estimated $R_t$ in the past 15 days:

ML Low_90 High_90 Low_50 High_50
county date
Harris 2020-08-25 0.90 0.71 1.05 0.81 0.95
2020-08-26 0.93 0.75 1.09 0.85 0.99
2020-08-27 1.04 0.86 1.20 0.95 1.09
2020-08-28 1.17 0.99 1.33 1.08 1.22
2020-08-29 1.25 1.08 1.41 1.15 1.29
2020-08-30 1.24 1.05 1.38 1.13 1.27
2020-08-31 1.12 0.93 1.26 1.01 1.15
2020-09-01 0.97 0.79 1.12 0.87 1.01
2020-09-02 0.83 0.65 0.98 0.73 0.87
2020-09-03 0.77 0.57 0.91 0.67 0.81
2020-09-04 0.80 0.61 0.95 0.71 0.85
2020-09-05 0.77 0.57 0.92 0.69 0.83
2020-09-06 0.73 0.54 0.89 0.62 0.77
2020-09-07 0.66 0.46 0.82 0.56 0.71
2020-09-08 0.54 0.35 0.71 0.45 0.60

Daily new cases and real time $R_t$ for all Texas counties

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Most recent $R_t$ by county

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